Included in the foregoing is an English version of the article
"L'âme au bout d'un rasoir, The
soul at the razor's edge", originally publised in the journal
Les Cahiers de l'Analyse des Données, vol. V, no. 2, 1980, pp. 229-242.
Updated version (10 May 2009) in English of this article,
"L'âme au bout d'un rasoir, The soul at the razor's edge".

J.P. Benzécri, from Foreword:
"Physics progresses, mainly, by constituting corpora of rare
phenomena among immense sets of ordinary cases. The simple
observation of one of these ordinary cases requires detection
apparatus based on millions of small elementary detectors.
Yet physics is, in part, a computational science, as evidenced
by the conclusion of a paper on the theory of generalized zeta
functions: "Our results are secure, numerically, yet appear very
hard to prove by analysis".
I repeat: the statistician has to be modest. The work of my generation
has been exalting. A new statistical and data analysis is there to be
invented, now that one has inexpensive means of computation that could
not be dreamed of just thirty years ago."

Some of the programs, especially
the R and C ones, are in ascii text. Some others
are binary (e.g. the clustering DLL program, and the Java class files).
The Java code and the data sets are collected together in tar files, to
be extracted using WinZIP or tar or some similar utility.

Data sets to be used with R programs.
Currently 3 data sets (but see also the data sets available below that are
ready for use with the Java program: these can also be easily prepared for
use with the R programs).

2. Text Processing

The text processing support programs are all in C.

Analysis of multiple text files.

aviation-reports-data.tar,
47 aviation accident reports, the list of these files, programs
txtanalysis.c and xtabulate.c, and output files words.txt, words0.txt,
and xtabulate.txt, used as examples in the following.

word_analysis.c, program to check
for sufficient number of occurrences of words in all texts. Hence,
this program yields a common word-list. This common word-list can be
used by xtabulate.

Analysis of a single (large) text file.

arist10.txt, Aristotle's Categories.
Note: we removed the legal information (so as not to influence the
analysis) to yield the file arist10x.txt.

docanalysis.c program, to produce a word
list from a single text file. Example of use: docanalysis
arist10x.txt words.txt. for the Categories 1260 words are found.
It is best to filter or cull these (or else the cross-tabulations, to
follow will be very large).

doctabulate.c program, to produce a
cross-tabulation for each of the chapter and section levels in the
Categories. Use: doctabulate arist10x.txt words.txt out. This
produces the cross-tabulations, or contingency tables, out1.txt,
out2.txt, out3.txt, out4.txt, corresponding to the different section
levels in this book.

Notes: programs txtanalysis and xtabulate should handle acceptably
(i) accented characters, and (ii) use in a Mac OS X environment. (The
latter issue is that memory allocation is already catered for; so
the line "#include <malloc.h>" at the
start of the file should not be present.)

Tar file containing all *.class class
files. Run these using the JRE (Java Runtime Environment) command:
java DataAnalysis
It is best to do this as a command-line instruction, in the classes
directory. A pop-up window will prompt for the input file name.

4. Updates to the Book

Errata

P. 37, line -14, change f_K to
f_I. And in paragraphs on lines -11, -10, delete opening words and
terms to begin sentence with: We can right-multiply the
eigen-equation above ....

P. 113, line 6 of text, 40% should be 48%.

See above for changes to the C program for hierarchical clustering
(minimum variance/Wards with weighting of rows/cases), and associated R
calling script.

Updates

A new version of facor, with an example of
use at the start of the program. Input data set,
casa2.prn (text file), a characterization with 13 person and place
attributes of the 77 scenes of the film, Casablanca.

5. Book Reviews and Survey Papers

"Detailed examples of its application to data are drawn from an astonishingly wide variety of fields; astronomy,
financial modeling and forecasting, comparisons of prehistoric and modern groups of dogs, ancient goblets and measurements
on ancient Egyptian skulls. ... All in all this book can be recommended as a succinct reference on all aspects of correspondence
analysis, theoretical, computational, and practical." - J.M. Juritz, Short Book Reviews of the ISI.

"This book plays an important role in bridging the gap between learning a method and actually implementing it ... could
serve as either a text for an introductory course on CA or as a supplementary text to a more advanced graduate course in CA or
multivariate techniques in general ... The author should be commended for bringing these issues to the forefront."
– Douglas Steinley, University of Missouri-Columbia, in Psychometrika, Vol. 74, No. 1, 2007.